Title :

SHREC 2019 Track: Online Gesture Recognition

Author(s) :

Caputo, F [Auteur]
Burato, S [Auteur]
Pavan, G [Auteur]
Giachetti, A [Auteur]
Voillemin, Théo [Auteur]
Ecole nationale supérieure Mines-Télécom Lille Douai [IMT Nord Europe]
Centre for Digital Systems [CERI SN - IMT Nord Europe]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Wannous, Hazem [Auteur correspondant]
Ecole nationale supérieure Mines-Télécom Lille Douai [IMT Nord Europe]
Centre for Digital Systems [CERI SN - IMT Nord Europe]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Vandeborre, Jean-Philippe [Auteur]
Ecole nationale supérieure Mines-Télécom Lille Douai [IMT Nord Europe]
Centre for Digital Systems [CERI SN - IMT Nord Europe]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Maghoumi, M [Auteur]
NVIDIA [NVIDIA]
Taranta, E M [Auteur]
Razmjoo, A [Auteur]
La Viola, J.J [Auteur]
Manganaro, F [Auteur]
Pini, S [Auteur]
Borghi, G [Auteur]
Vezzani, R [Auteur]
Cucchiara, R [Auteur]
Nguyen, H [Auteur]
Tran, M [Auteur]

Conference title :

Eurographics Workshop on 3D Object Retrieval

City :

Genova

Country :

Italie

Start date of the conference :

2019-05-05

Book title :

Eurographics Workshop on 3D Object Retrieval

English keyword(s) :

Human-centered computing
Gestural input

HAL domain(s) :

Informatique [cs]/Vision par ordinateur et reconnaissance de formes [cs.CV]
Informatique [cs]/Interface homme-machine [cs.HC]

English abstract : [en]

This paper presents the results of the Eurographics 2019 SHape Retrieval Contest track on online gesture recognition. The goal of this contest was to test state-of-the-art methods that can be used to online detect command ...
Show more >This paper presents the results of the Eurographics 2019 SHape Retrieval Contest track on online gesture recognition. The goal of this contest was to test state-of-the-art methods that can be used to online detect command gestures from hands' movements tracking on a basic benchmark where simple gestures are performed interleaving them with other actions. Unlike previous contests and benchmarks on trajectory-based gesture recognition, we proposed an online gesture recognition task, not providing pre-segmented gestures, but asking the participants to find gestures within recorded trajectories. The results submitted by the participants show that an online detection and recognition of sets of very simple gestures from 3D trajectories captured with a cheap sensor can be effectively performed. The best methods proposed could be, therefore, directly exploited to design effective gesture-based interfaces to be used in different contexts, from Virtual and Mixed reality applications to the remote control of home devices.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL